Upper ontology design for application based spatial ontologies
Download
1 / 18

Upper Ontology Design for Application-Based Spatial Ontologies - PowerPoint PPT Presentation


  • 147 Views
  • Uploaded on

Upper Ontology Design for Application-Based Spatial Ontologies. Eric Little, PhD D’Youville College National Center for Ontology Research (NCOR) National Center for Multisource Information Fusion (NCMIF) Buffalo, NY USA [email protected] [email protected] The Structure of an Ontology.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Upper Ontology Design for Application-Based Spatial Ontologies' - john


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Upper ontology design for application based spatial ontologies

Upper Ontology Design for Application-Based Spatial Ontologies

Eric Little, PhD

D’Youville College

National Center for Ontology Research (NCOR)

National Center for Multisource Information Fusion (NCMIF)

Buffalo, NY USA

[email protected]

[email protected]


The structure of an ontology
The Structure of an Ontology Ontologies

  • Upper-Level (Formal):

    • Most general categories of existence (e.g., existent item, spatial region, dependent part).

    • This Level of the ontology is rationally driven, meaning it is the product of philosophical reasoning.

    • Relies on a sound metaphysical description of the world (e.g., realism).


The structure of an ontology1
The Structure of an Ontology Ontologies

  • Domain-Specific Level

    • Contains categories that are specific to a particular domain of interest (disaster, military/defense, medicine).

    • This level of the ontology is empirically driven, meaning it is produced by gathering expert knowledge about a given domain of interest.

    • The expert knowledge is used to create a consistent and comprehensive lexicon of terms.



Ontologies vs taxonomies
Ontologies vs. Taxonomies Ontologies

Urban Environment

Taxonomy

IED Taxonomy

Dirty Bomb

Taxonomy

ETC…

Taxonomy A

Taxonomy B

Taxonomy C

ONTOLOGY


Using knowledge representation reasoning krr to conjoin taxonomies

SPAN Taxonomy (Temporal Items) Ontologies

SNAP Taxonomy (Spatial Items)

Using Knowledge Representation & Reasoning (KRR) to Conjoin Taxonomies

Transcategorical Relations

Represented in KRR

Example:

An Intentional Act is a Psychological Act

that depends on an agent to instantiate it.

It stands in a relation of dependence to

other items such as neuro-biological

states.


Relating ontology to other engineering practices
Relating Ontology to Other Engineering Practices Ontologies

  • Ontologies informthe design of other engineering systems (e.g., agent-based sys, decision support sys, predictive analytics, etc.) by providing a structured comprehensive picture of their domains.

    • Many engineering practices require a more principled basis for their design.

  • Engineering systems constrain the ontology by providing inputs such as:

    • User needs

    • Domain specificity

    • Computational tractability

      • If you give philosophers carte blanche, remember … fools and their $ are easily parted.


Higher level fusion
Higher Level Fusion Ontologies

The purpose of higher level fusion is to develop probable explanations of a situation based on prior knowledge and incoming transient information to produce a coherent composite picture of the current situation along with a prediction of consequences.

A dynamic situational picture is the result of reasoning about objects, attributes, aggregates, relationships and their behavior over time within a specific context.

The process of building the dynamic situational picture requires formally structured and computationally tractable domain representation.


What kinds of ontologies are needed for high level fusion sta
What kinds of ontologies are needed for High-level fusion & STA?

  • Low – level fusion can be done (to a large degree) using existing tools such as OWL, Protégé, DAML - Oil, etc.

  • However, higher-level fusion processing is concerned with providing comprehensive and consistent descriptions of highly complex world states.

  • Hence we need a more “industrial strength” (cf. Musen) approach than is provided by current fusion ontologies.


Relations between situational objects at different levels of granularity
Relations Between Situational Objects at Different Levels of Granularity

  • Inter - Relationships: 1) Relationships between situational items of different types. 2) Relationships between items and aggregates of items of a different type. 3) relationships between aggregates of objects of different types

  • Intra - Relationships: 1) Relationships between different physical objects or their respective attributes/properties. 2) Relationships between different clusters/aggregates of objects in the same group.

Physical objects –

Physical objects (PO-PO)

Combinations of ES (CES) –

Combinations of ES

Interclass

Intraclass

Temporal

Spatial

PO- Aggregates of PO

Elementary Situation

-Elementary situation

(ES-ES)

Relations

Aggregates- Aggregates

CES-ES

Processes-Processes

(process aggregation)

Events-Events

(event aggregation)


Ontologize this
Ontologize this… Granularity

Frank White (Workshop II on Ontologies and Higher-lvl Fusion – Beaver Hollow


Existing fusion ontology models often confuse various kinds of relations
Existing fusion ontology models often confuse various kinds of relations

Temporal Relations

Spatial Relations

Situation Awareness (SAW) Ontology Model for Battlefield Relations

(C. J. Matheus, M. M. Kokar, and K. Baclawski. (2003)


It gets worse
It gets worse… of relations

Complex Relation

Type


Examples of important relationships

Relationships between time points of relations

Before, At the same time, Start, Finish, Soon, Very soon, Resulting in, Initiating

Relationships between time intervals

Disjoint, Joint, Overlap, Inside, Equal

SNAP relations

Topology/

mereology

Direction

Distance

Size

Along

Towards

East

West

South

North

Similar

Opposite

Disjoint

Joint

Overlap

Cover

Reachable

Unreachable

Contain

A part of

Far

Very far

Near

Very near

Small (er)

Large(r)

Same

Disaster Examples:

“Close to a hospital”

“Cluster A is larger than before”

“Along the wind direction”

“Distance between Clusters A and B is smaller than before”

“Casualty cluster A overlaps with building cluster C”

Examples of Important Relationships

SPAN relations


Building reasoning processes with ontologies

  • SNAP of relations

  • Ontology

  • Spatial Items

  • Of Interest

  • SPAN

  • Ontology

  • Temporal Items

  • Of Interest

Building Reasoning Processes with Ontologies

FUSION

Reasoning about

relations represented

in Ontology

Transcategorical

Ontology

(Objects + Processes)




Small representative sample of the snap dis reo ontology w cwa
Small Representative Sample of the SNAP Dis-ReO Ontology w/ CWA

Bisantz, A., Rogova, G., Little, E. (2004) “On the Integration of Cognitive Work Analysis within a

Multisource Information Fusion Development Methodology,” Proceedings of the Human Factors and

Ergonomics Society Annual Meeting, New Orleans


ad